Robust Coverless Image Steganography Based on DCT and LDA Topic Classification

Zhang, Xiang; Peng, Fei; Long, Min

doi:10.1109/tmm.2018.2838334

Cited by 184 publications

(117 citation statements)

References 36 publications

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“…More recently, Jiang et al designed a reversible data hiding in encrypted domain scheme with low computational complexity for three-dimensional meshes [20]. Zhang et al suggested a coverless steganographic algorithm based on discrete cosine transform and latent dirichlet allocation topic classification, having robustness against common image processing and better ability to resist steganalysis [21].…”

Section: Related Workmentioning

confidence: 99%

Security of Streaming Media Communications with Logistic Map and Self-Adaptive Detection-Based Steganography

Peng

Jiang

Tang

et al. 2019

IEEE Trans. Dependable and Secure Comput.

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S e c u ri ty of S t r e a m i n g M e di a Co m m u ni c a tio n s wi t h Lo gi s tic M a p a n d S elf-Ad a p tiv e D e t e c tio n-B a s e d S t e g a n o g r a p h y P e n g, J, Jia n g, Y, Tan g, S a n d M e zi a n e, F h t t p:// dx. doi.o r g/ 1 0. 1 1 0 9/TD SC. 2 0 1 9. 2 9 4 6 1 3 8Ti t l e S e c u ri ty of S t r e a mi n g M e di a Co m m u ni c a tio n s wit h Lo gis tic M a p a n d S elf-Ad a p tiv e D e t e c tio n-B a s e d S t e g a n o g r a p hy A u t h o r s P e n g, J, Jia n g, Y, Ta n g, S a n d M e zi a n e , F Typ e Articl e U RL This ve r sio n is a v ail a bl e a t : h t t p:// u sir.s alfo r d. a c. u k/id/ e p ri n t/ 5 2 6 6 0/ P u b l i s h e d D a t e 2 0 1 9 U SIR is a di git al c oll e c tio n of t h e r e s e a r c h o u t p u t of t h e U niv e r si ty of S alfo r d. W h e r e c o py ri g h t p e r mi t s, full t e x t m a t e ri al h el d in t h e r e p o si to ry is m a d e fr e ely a v ail a bl e o nli n e a n d c a n b e r e a d , d o w nlo a d e d a n d c o pi e d fo r n o nc o m m e r ci al p riv a t e s t u dy o r r e s e a r c h p u r p o s e s . Pl e a s e c h e c k t h e m a n u s c ri p t fo r a n y fu r t h e r c o py ri g h t r e s t ri c tio n s. Fo r m o r e info r m a tio n, in cl u di n g o u r p olicy a n d s u b mi s sio n p r o c e d u r e , pl e a s e c o n t a c t t h e R e p o si to ry Te a m a t: u si r@ s alfo r d. a c. u k .Abstract-Voice over IP (VoIP) is finding its way into several applications, but its security concerns still remain. This paper shows how a new self-adaptive steganographic method can ensure the security of covert VoIP communications over the Internet. In this study an Active Voice Period Detection algorithm is devised for PCM codec to detect whether a VoIP packet carries active or inactive voice data, and the data embedding location in a VoIP stream is chosen randomly according to random sequences generated from a logistic chaotic map. The initial parameters of the chaotic map and the selection of where to embed the message are negotiated between the communicating parties. Steganography experiments on active and inactive voice periods were carried out using a VoIP communications system. Performance evaluation and security analysis indicates that the proposed VoIP steganographic scheme can withstand statistical detection, and achieve secure real-time covert communications with high speech quality and negligible signal distortion.

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Section: Related Workmentioning

confidence: 99%

Security of Streaming Media Communications with Logistic Map and Self-Adaptive Detection-Based Steganography

Peng

Jiang

Tang

et al. 2019

IEEE Trans. Dependable and Secure Comput.

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“…The algorithm proposed in Liu et al [Liu, Zhang, Liu et al (2018); Duan and Song (2018)] combined the coverless information hiding algorithm with machine learning, and used the generated model to generate images related to secret information for transmission. The paper Zhang et al [Zhang, Peng and Long (2018)] generated the feature sequence through the relation between Direct Current coefficients in the adjacent blocks.…”

Section: Related Workmentioning

confidence: 99%

“…We compare our embedding capacity with four existing coverless image steganography methods. Their approaches are coverless image steganography using partial-duplicate visual retrieval [Zhou, Mu and Wu (2017)], denoted as CIS-PDVR, coverless image steganography method based on bag-of-words [Zhou, Cao and Sun (2016)], denoted as CIS-BOW, coverless image steganography based on SIFT and BOF [Yuan, Xia and Sun (2017)], denoted as CIS-BOF and robust coverless image steganography based on DCT and LDA [Zhang, Peng and Long (2018)], denoted as CIS-DCT. So far, the largest capacity is the method proposed in CIS-PDVR.…”

Section: Capacity Of Steganographymentioning

confidence: 99%

Coverless Image Steganography Method Based on Feature Selection

Qiu¹,

Chen

Sun³

et al. 2019

Journal of Information Hiding and Privacy Protection

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A new information hiding technology named coverless information hiding is proposed. It uses original natural images as stego images to represent secret information. The focus of coverless image steganography method is how to represent image features and establish a map relationship between image feature and the secret information. In this paper, we use three kinds of features which are Local Binary Pattern (LBP), the mean value of pixels and the variance value of pixels. On this basis, we realize the transmission of secret information. Firstly, the hash sequence of the original cover image is obtained according to the description of the feature, and then the sequence of the secret information and the hash sequence of the original cover image are matched one by one. If the values are not the same, the image blocks of the original cover image are replaced according to the secret information to get the stego image. This paper explores the effect of three features on the visual quality of stego image. Experimental results show that the feature LBP is the best.

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“…More recently, machine learning based approaches have been considered to generate covers for steganography [7,34,36]. In [44], Zhang et al proposed a coverless steganography method based on Discrete Cosine Transform (DCT) and Latent Dirichlet Allocation (LDA) topic classification, where images that each represent a segment of the hidden message are selected from a database.…”

Section: Generative (Coverless) Information Hidingmentioning

confidence: 99%

“…Therefore, it is necessary to invent new steganographic methods to make information hiding more secure. One new approach called generative (also known as coverless) information hiding is to move away from using a selected (pre-existing) cover object, but to embed hidden data into one or more generated objects that did not exist [7,26,27,34,36,38,41,44].…”

Section: Introductionmentioning

confidence: 99%

Lost in the Digital Wild

Wang

et al. 2018

Proceedings of the 2nd International Workshop on Multimedia Privacy and Security

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This paper presents a new general framework of information hiding, in which the hidden information is embedded into a collection of activities conducted by selected human and computer entities (e.g., a number of online accounts of one or more online social networks) in a selected digital world. Different from other traditional schemes, where the hidden information is embedded into one or more selected or generated cover objects, in the new framework the hidden information is embedded in the fact that some particular digital activities with some particular attributes took place in some particular ways in the receiver-observable digital world.In the new framework the concept of "cover" almost disappears, or one can say that now the whole digital world selected becomes the cover. The new framework can find applications in both security (e.g., steganography) and non-security domains (e.g., gaming). For security applications we expect that the new framework calls for completely new steganalysis techniques, which are likely more complicated, less effective and less efficient than existing ones due to the need to monitor and analyze the whole digital world constantly and in real time. A proof-of-concept system was developed as a mobile app based on Twitter activities to demonstrate the information hiding framework works. We are developing a more hybrid system involving several online social networks.

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Robust Coverless Image Steganography Based on DCT and LDA Topic Classification

Cited by 184 publications

References 36 publications

Security of Streaming Media Communications with Logistic Map and Self-Adaptive Detection-Based Steganography

Security of Streaming Media Communications with Logistic Map and Self-Adaptive Detection-Based Steganography

Coverless Image Steganography Method Based on Feature Selection

Lost in the Digital Wild

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